Abstract

PurposeInherited variants in the cancer susceptibility genes, BRCA1 and BRCA2 account for up to 5% of breast cancers. Multiple gene expression studies have analysed gene expression patterns that maybe associated with BRCA12 pathogenic variant status; however, results from these studies lack consensus. These studies have focused on the differences in population means to identified genes associated with BRCA1/2-carriers with little consideration for gene expression variability, which is also under genetic control and is a feature of cellular function.MethodsWe measured differential gene expression variability in three of the largest familial breast cancer datasets and a 2116 breast cancer meta-cohort. Additionally, we used RNA in situ hybridisation to confirm expression variability of EN1 in an independent cohort of more than 500 breast tumours.ResultsBRCA1-associated breast tumours exhibited a 22.8% (95% CI 22.3–23.2) increase in transcriptome-wide gene expression variability compared to BRCAx tumours. Additionally, 40 genes were associated with BRCA1-related breast cancers that had ChIP-seq data suggestive of enriched EZH2 binding. Of these, two genes (EN1 and IGF2BP3) were significantly variable in both BRCA1-associated and basal-like breast tumours. RNA in situ analysis of EN1 supported a significant (p = 6.3 × 10−04) increase in expression variability in BRCA1-associated breast tumours.ConclusionOur novel results describe a state of increased gene expression variability in BRCA1-related and basal-like breast tumours. Furthermore, genes with increased variability may be driven by changes in DNA occupancy of epigenetic effectors. The variation in gene expression is replicable and led to the identification of novel associations between genes and disease phenotypes.

Highlights

  • Gene expression profiles have been used extensively in the study of cancer development, treatment response and prognosis

  • Using gene-specific standard deviations, BRCA1-associated breast tumours had a 22.8% increase in gene expression variability

  • Increased variability in BRCA1associated breast tumours was observed in linear models of gene-specific coefficient of variance (CV) (25.0%, 95% CI 24.5–25.6) and median absolute deviation (MAD) (32.4%, 95% CI 31.9–33.0)

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Summary

Introduction

Gene expression profiles have been used extensively in the study of cancer development, treatment response and prognosis. A few studies have been reported to date, this approach has led to the identification of a pan-cancer gene set [16], a classifier for chronic lymphocytic leukaemia [17] and synthetic lethal genes in BRCA2-associated ovarian tumours [18]. These studies measured gene expression variability of wholetranscriptome data generated from microarray or RNAsequencing platforms. The ER status of breast tumours was later identified to be a major driver of gene expression changes [3] These studies have overlooked the variability in gene expression and whether these phenotypes are associated with the presence of a pathogenic variant

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